{
 "cells": [
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   "source": [
    "## grandlib installation\n",
    "In last version of GRANDLIB package,there is a reorganization of the code and to avoid the presence of unused empty directory, it is advisable to perform a git clone rather than a git fetch/pull.\n",
    "See [here](https://github.com/grand-mother/grand/wiki) the installation procedure.\n",
    "\n",
    "\n",
    "### grandlib structure\n",
    "\n",
    "<details>\n",
    "<summary>&emsp;&emsp;Click here to expand/hide</summary>\n",
    "\n",
    "```\n",
    "binder\n",
    "    ├── readme.md\n",
    "    ├── requirements.txt\n",
    "    ├── Dockerfile\n",
    "    └── Dockerfile_all\n",
    "data\n",
    "    ├── download_data_grand.py\n",
    "    ├── grand_model_2207.tar.gz\n",
    "    ├── egm96.png\n",
    "    ├── test_efield.root\n",
    "    ├── detector\n",
    "    │   ├── Light_GP300Antenna_EWarm_leff.npy\n",
    "    │   ├── Light_GP300Antenna_SNarm_leff.npy\n",
    "    │   ├── Light_GP300Antenna_Zarm_leff.npy\n",
    "    │   ├── HorizonAntenna_EWarm_leff_loaded.npy\n",
    "    │   ├── HorizonAntenna_SNarm_leff_loaded.npy\n",
    "    │   ├── HorizonAntenna_Zarm_leff_loaded.npy\n",
    "    │   ├── LNASparameter\n",
    "    │   │   ├── 1.s2p\n",
    "    │   │   ├── 2.s2p\n",
    "    │   │   └── 3.s2p\n",
    "    │   ├── antennaVSWR\n",
    "    │   │   ├── 1.s1p\n",
    "    │   │   ├── 2.s1p\n",
    "    │   │   └── 3.s1p\n",
    "    │   ├── cableparameter\n",
    "    │   │   └── cable.s2p\n",
    "    │   └── filterparameter\n",
    "    │       └── 1.s2p\n",
    "    ├── geomagnet\n",
    "    │   ├── IGRF13.COF\n",
    "    │   └── WMM2020.COF\n",
    "    └── sky\n",
    "    │   └── 30_250galactic.mat\n",
    "    ├── topography\n",
    "    │   └── ---\n",
    "    └── readme.md\n",
    "docs\n",
    "    ├── requirements.txt\n",
    "    ├── grandlib_classes_v2.pdf\n",
    "    ├── grandlib_structure.pdf\n",
    "    ├── GRANDreferential.pdf\n",
    "    ├── GRANDscripts.pdf\n",
    "    ├── conf.py\n",
    "    ├── patch.py\n",
    "    ├── index.rst\n",
    "    ├── installation.rst\n",
    "    ├── Makefile\n",
    "    ├── algo\n",
    "    │   └── Leff_processing.md\n",
    "    ├── apidoc-only \n",
    "    │   ├── doxygen-rtd\n",
    "    │   └── sphinx\n",
    "    └── package\n",
    "    │   ├── grand.coordinates.rst\n",
    "    │   ├── grand.geomagnet.rst\n",
    "    │   ├── grand.io.rst\n",
    "    │   ├── grand.rst\n",
    "    │   ├── grand.simulation.rst\n",
    "    │   ├── grand.store.rst\n",
    "    │   └── grand.topography.rst\n",
    "    └── readme.md\n",
    "env\n",
    "    ├── conda\n",
    "    │   └── grand_user.yml\n",
    "    ├── docker_fedo \n",
    "    │   └── ---\n",
    "    ├── docker_root \n",
    "    │   └── ---\n",
    "    ├── _setup_env.sh\n",
    "    ├── _setup_lib.sh\n",
    "    ├── setup.sh\n",
    "    └── readme.md\n",
    "examples \n",
    "    ├── geo\n",
    "    │   ├── trial_GP300_layout_2021.txt\n",
    "    │   ├── __init__.py\n",
    "    │   ├── GP100_topography.py\n",
    "    │   ├── local_topography.py\n",
    "    │   ├── grids.py\n",
    "    │   ├── hexy.py\n",
    "    │   ├── coordinates_tutorial.ipynb\n",
    "    │   ├── geomagnet_tutorial.ipynb\n",
    "    │   └── topography_tutorial.ipynb\n",
    "    ├── io\n",
    "    │   ├── __init__.py\n",
    "    │   ├── data_reading.py\n",
    "    │   ├── data_storing.py\n",
    "    │   └── readme.md \n",
    "    ├── simulation \n",
    "    │   ├── rf_chain_example.py\n",
    "    │   ├── shower_event.py\n",
    "    │   ├── antenna.ipynb\n",
    "    │   ├── coreas.ipynb\n",
    "    │   ├── galactic_noise.ipynb\n",
    "    │   ├── rf_chain_example.ipynb\n",
    "    │   ├── shower_event.ipynb\n",
    "    │   └── zhaires.ipynb\n",
    "    └── __init__.py\n",
    "grand\n",
    "    ├── manage_log.py\n",
    "    ├── __init__.py \n",
    "    ├── basis\n",
    "    │   ├── __init__.py\n",
    "    │   ├── du_network.py\n",
    "    │   ├── traces_event.py\n",
    "    │   └── type_trace.py        \n",
    "    ├── geo\n",
    "    │   ├── __init__.py\n",
    "    │   ├── coordinates.py\n",
    "    │   ├── geomagnet.py\n",
    "    │   ├── gull.py\n",
    "    │   ├── turtle.py\n",
    "    │   └── topography.py\n",
    "    ├── io          \n",
    "    │   ├── README.md\n",
    "    │   ├── __init__.py\n",
    "    │   ├── io_node.py\n",
    "    │   ├── pipeline.py\n",
    "    │   ├── protocol.py\n",
    "    │   ├── root_files.py\n",
    "    │   └── root_trees.py\n",
    "    ├── num\n",
    "    │   ├── __init__.py\n",
    "    │   └── signal.py\n",
    "    ├── recons\n",
    "    │   ├── __init__.py\n",
    "    │   ├── elec_field.py\n",
    "    │   └── params_shower.py\n",
    "    ├── simu\n",
    "    │   ├── __init__.py\n",
    "    │   ├── efield2voltage.py\n",
    "    │   ├── du\n",
    "    │   │   ├── __init__.py\n",
    "    │   │   ├── antenna_model.py\n",
    "    │   │   └── process_ant.py\n",
    "    │   ├── noise\n",
    "    │   │   ├── galaxy.py\n",
    "    │   │   └── rf_chain.py\n",
    "    │   └── shower\n",
    "    │       ├── __init__.py\n",
    "    │       ├── coreas.py\n",
    "    │       ├── gen_shower.py\n",
    "    │       ├── pdg.py\n",
    "    │       ├── zhaires.py\n",
    "    └── _core.abi3.so        \n",
    "granddb  \n",
    "    ├── granddatalib.py\n",
    "    ├── testssh.py\n",
    "    └── config.ini\n",
    "lib\n",
    "    ├── readme.md\n",
    "    ├── libgull.so\n",
    "    └── libturtle.so\n",
    "quality  \n",
    "    ├── requirements.txt\n",
    "    ├── check_score_coverage.py\n",
    "    ├── grand_quality_all.bash\n",
    "    ├── grand_quality_analysis.bash\n",
    "    ├── grand_quality_clean.bash\n",
    "    ├── grand_quality_format.bash\n",
    "    ├── grand_quality_test_cov.bash\n",
    "    ├── grand_quality_type.bash\n",
    "    ├── mypy.conf\n",
    "    ├── pylint.conf\n",
    "    └── ci\n",
    "    │   ├── apply_sonar_update.bash\n",
    "    │   ├── coverage_if_necessary.bash\n",
    "    │   ├── manage_sonar_update.py\n",
    "    │   └── pylint_ci.conf\n",
    "    └── readme.md\n",
    "scripts  \n",
    "    ├── grand_ioroot.py\n",
    "    ├── grand_plot_trace_all.py\n",
    "    ├── grand_plot_trace_first.py\n",
    "    ├── grand_simu_du.py\n",
    "    ├── MDanalysis_v0.py\n",
    "    ├── MDanalysis.py\n",
    "    ├── readReducedData.py\n",
    "    ├── backup\n",
    "    │   ├── grand_simu_du_xidian.py\n",
    "    │   └── lib_xidian.py\n",
    "    └── readme.md\n",
    "src\n",
    "    ├── build_core.py\n",
    "    ├── grand.c\n",
    "    ├── grand.h\n",
    "    ├── install_ext_lib.bash\n",
    "    ├── Makefile\n",
    "    └── build \n",
    "        ├── grand\n",
    "        │   └── ---\n",
    "        ├── include\n",
    "        │   └── ---\n",
    "        ├── lib\n",
    "        │   └── ---\n",
    "        ├── src\n",
    "        │   └── ---\n",
    "        └── tmp\n",
    "            └── ---\n",
    "src_outlib\n",
    "    ├── AiresInfoFunctionsGRANDROOT.py\n",
    "    ├── analyse_resp_antenna.py\n",
    "    ├── debug_plot.py\n",
    "    ├── test_FileSimuEfield.py\n",
    "    ├── test_io_root.py\n",
    "    ├── test_simu_dc1.py\n",
    "    ├── test_template.py\n",
    "    ├── test_trace.py\n",
    "    ├── trace.py\n",
    "    ├── use_root_tree.py\n",
    "    ├── widget.py\n",
    "    ├── xdu_rf_ref.py\n",
    "    ├── ZHAireSRawToGRANDROOT.py\n",
    "    ├── backup\n",
    "    │   ├── readme.md\n",
    "    │   ├── __init__.py\n",
    "    │   ├── signal_bkp.py\n",
    "    │   └── signal_ex.py\n",
    "    └── __init__.py\n",
    "tests\n",
    "    ├── __main__.py\n",
    "    ├── conftest_old.py\n",
    "    ├── test_manage_log.py\n",
    "    ├── basis\n",
    "    │   ├── __init__.py \n",
    "    │   ├── test_DetectorUnitNetwork.py\n",
    "    │   └── test_Handling3dTracesOfEvent.py\n",
    "    ├── core\n",
    "    │   ├── __init__.py\n",
    "    │   ├── __main__.py\n",
    "    │   └── test_io.py\n",
    "    ├── libs\n",
    "    │   ├── __init__.py\n",
    "    │   ├── __main__.py\n",
    "    │   ├── test_gull.py\n",
    "    │   ├── test_turtle.py\n",
    "    │   └── data \n",
    "    │       └── map.png\n",
    "    ├── simulation\n",
    "    │   ├── __init__.py\n",
    "    │   ├── __main__.py\n",
    "    │   ├── test_antenna.py\n",
    "    │   ├── test_shower.py\n",
    "    │   └── test_VgaFilterBalunGP300.py\n",
    "    ├── store          \n",
    "    │   ├── __init__.py\n",
    "    │   ├── __main__.py\n",
    "    │   └── test_protocol.py\n",
    "    ├── tools\n",
    "    │   ├── __init__.py\n",
    "    │   ├── __main__.py\n",
    "    │   ├── test_coordinates.py\n",
    "    │   ├── test_func_coordinates.py\n",
    "    │   ├── test_geomagnet.py\n",
    "    │   └── test_topography.py\n",
    "    └── __init__.py\n",
    "wheel\n",
    "    ├── build-linux-wheel.sh\n",
    "    ├── setup.py\n",
    "    └── Makefile\n",
    "```\n",
    "</details>\n",
    "\n",
    "</span>\n",
    "\n"
   ]
  },
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   "id": "64f3b635",
   "metadata": {},
   "source": [
    "***\n",
    "## grandlib in docker\n",
    "\n",
    "Install [docker](https://www.docker.com/products/docker-desktop/). \n",
    "docker 4.12 requires OS 10.15 and higher in mac. In this case, download the older version of docker, i.e. 4.11. Read [this tutorial](https://github.com/grand-mother/grand/wiki/docker_quickstart) to install docker and to get started depending on your operating system. Make sure to implement \"Enable graphics\" to view plots.\n",
    "\n",
    "After installing docker, run the latest version of grandlib (in terminal).\n",
    "```bash\n",
    "\t1. git clone https://github.com/grand-mother/grand.git\n",
    "\t2. cd grand\n",
    "\t3. docker run -p 8888:8888 -it -e DISPLAY=192.168.1.100:0 --name grandlib -v $PWD:/home grandlib/dev   \n",
    "                                 # -p 8888:8888 is needed for notebook.\n",
    "\t4. source env/setup.sh       # to install required data for grandlib and compile gull and turtle.\n",
    "    5. grand_jupyter             # run jupyter notebook. This notebook is created after running this command.\n",
    "```\n",
    "\n",
    "To re-run grandlib image:\n",
    "```bash\n",
    "\t6. docker start -ia grandlib\n",
    "```\n",
    "\n",
    "Step 4: \"source env/setup.sh\" gives the following output.\n",
    "```bash\n",
    "Set var GRAND_ROOT=/home/grand\n",
    "==============================\n",
    "add grand/quality to PATH\n",
    "==============================\n",
    "add grand to PYTHONPATH\n",
    "==============================\n",
    "Install external lib gull and turtle\n",
    "==============================\n",
    "...\n",
    "==============================\n",
    "Download data model (~ 350MB) for GRAND, please wait ...\n",
    "Successfully downloaded\n",
    "==============================\n",
    "Extract tar file\n",
    "data model available in grand/data directory !\n",
    "```"
   ]
  },
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   "metadata": {},
   "source": [
    "### ROOT File structure:\n",
    "\n",
    "&emsp;**TRun:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (23)</summary>\n",
    "        &emsp;&emsp;1. run_number\\\n",
    "        &emsp;&emsp;2. run_mode\\\n",
    "        &emsp;&emsp;3. first_event\\\n",
    "        &emsp;&emsp;4. first_event_time\\\n",
    "        &emsp;&emsp;5. last_event\\\n",
    "        &emsp;&emsp;6. last_event_time\\\n",
    "        &emsp;&emsp;7. data_source\\\n",
    "        &emsp;&emsp;8. data_generator\\\n",
    "        &emsp;&emsp;9. data_generator_version\\\n",
    "        &emsp;&emsp;10. event_type\\\n",
    "        &emsp;&emsp;11. event_version\\\n",
    "        &emsp;&emsp;12. site\\\n",
    "        &emsp;&emsp;13. site_layout\\\n",
    "        &emsp;&emsp;14. origin_geoid\\\n",
    "        &emsp;&emsp;15. du_id\\\n",
    "        &emsp;&emsp;16. du_geoid\\\n",
    "        &emsp;&emsp;17. du_xyz\\\n",
    "        &emsp;&emsp;18. du_type\\\n",
    "        &emsp;&emsp;19. du_tilt\\\n",
    "        &emsp;&emsp;20. du_ground_tilt\\\n",
    "        &emsp;&emsp;21. du_nut\\\n",
    "        &emsp;&emsp;22. du_feb\\\n",
    "        &emsp;&emsp;23. t_bin_size\\\n",
    "    </details>\n",
    "\n",
    "&emsp;**TRunNoise:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (3)</summary>\n",
    "        &emsp;&emsp;24. gal_noise_map\\\n",
    "        &emsp;&emsp;25. gal_noise_LST\\\n",
    "        &emsp;&emsp;26. gal_noise_sigma\\\n",
    "    </details>\n",
    "\n",
    "&emsp;**TRunVoltage:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (18)</summary>\n",
    "        &emsp;&emsp;27. run_number\\\n",
    "        &emsp;&emsp;28. digi_ctrl\\\n",
    "        &emsp;&emsp;29. firmware_version\\\n",
    "        &emsp;&emsp;30. trace_length\\\n",
    "        &emsp;&emsp;31. trigger_position\\\n",
    "        &emsp;&emsp;32. adc_sampling_frequency\\\n",
    "        &emsp;&emsp;33. adc_sampling_resolution\\\n",
    "        &emsp;&emsp;34. adc_input_channels\\\n",
    "        &emsp;&emsp;35. adc_enabled_channels\\\n",
    "        &emsp;&emsp;36. gain\\\n",
    "        &emsp;&emsp;37. adc_conversion\\\n",
    "        &emsp;&emsp;38. digi_prepost_trig_windows\\\n",
    "        &emsp;&emsp;39. channel_properties_x\\\n",
    "        &emsp;&emsp;40. channel_properties_y\\\n",
    "        &emsp;&emsp;41. channel_properties_z\\\n",
    "        &emsp;&emsp;42. channel_trig_settings_x\\\n",
    "        &emsp;&emsp;43. channel_trig_settings_y\\\n",
    "        &emsp;&emsp;44. channel_trig_settings_z\\\n",
    "    </details>\n",
    "\n",
    "&emsp;**TADC:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (59)</summary>\n",
    "        &emsp;&emsp; 45. run_number\\\n",
    "        &emsp;&emsp; 46. event_number\\\n",
    "        &emsp;&emsp; 47. event_size\\\n",
    "        &emsp;&emsp; 48. t3_number\\\n",
    "        &emsp;&emsp; 49. first_du\\\n",
    "        &emsp;&emsp; 50. time_seconds\\\n",
    "        &emsp;&emsp; 51. time_nanoseconds\\\n",
    "        &emsp;&emsp; 52. event_type\\\n",
    "        &emsp;&emsp; 53. event_version\\\n",
    "        &emsp;&emsp; 54. du_count\\\n",
    "        &emsp;&emsp; 55. event_id\\\n",
    "        &emsp;&emsp; 56. du_id\\\n",
    "        &emsp;&emsp; 57. du_seconds\\\n",
    "        &emsp;&emsp; 58. du_nanoseconds\\\n",
    "        &emsp;&emsp; 59. trigger_position\\\n",
    "        &emsp;&emsp; 60. trigger_flag\\\n",
    "        &emsp;&emsp; 61. atm_temperature\\\n",
    "        &emsp;&emsp; 62. atm_pressure\\\n",
    "        &emsp;&emsp; 63. atm_humidity\\\n",
    "        &emsp;&emsp; 64. acceleration_x\\\n",
    "        &emsp;&emsp; 65. acceleration_y\\\n",
    "        &emsp;&emsp; 66. acceleration_z\\\n",
    "        &emsp;&emsp; 67. battery_level\\\n",
    "        &emsp;&emsp; 68. firmware_version\\\n",
    "        &emsp;&emsp; 69. adc_sampling_frequency\\\n",
    "        &emsp;&emsp; 70. adc_sampling_resolution\\\n",
    "        &emsp;&emsp; 71. adc_input_channels\\\n",
    "        &emsp;&emsp; 72. adc_enabled_channels\\\n",
    "        &emsp;&emsp; 73. adc_samples_count_total\\\n",
    "        &emsp;&emsp; 74. adc_samples_count_channel0\\\n",
    "        &emsp;&emsp; 75. adc_samples_count_channel1\\\n",
    "        &emsp;&emsp; 76. adc_samples_count_channel2\\\n",
    "        &emsp;&emsp; 77. adc_samples_count_channel3\\\n",
    "        &emsp;&emsp; 78. trigger_pattern\\\n",
    "        &emsp;&emsp; 79. trigger_rate\\\n",
    "        &emsp;&emsp; 80. clock_tick\\\n",
    "        &emsp;&emsp; 81. clock_ticks_per_second\\\n",
    "        &emsp;&emsp; 82. gps_offset\\\n",
    "        &emsp;&emsp; 83. gps_leap_second\\\n",
    "        &emsp;&emsp; 84. gps_status\\\n",
    "        &emsp;&emsp; 85. gps_alarms\\\n",
    "        &emsp;&emsp; 86. gps_warnings\\\n",
    "        &emsp;&emsp; 87. gps_time\\\n",
    "        &emsp;&emsp; 88. gps_long\\\n",
    "        &emsp;&emsp; 89. gps_lat\\\n",
    "        &emsp;&emsp; 90. gps_alt\\\n",
    "        &emsp;&emsp; 91. gps_temp\\\n",
    "        &emsp;&emsp; 92. digi_ctrl\\\n",
    "        &emsp;&emsp; 93. digi_prepost_trig_windows\\\n",
    "        &emsp;&emsp; 94. channel_properties0\\\n",
    "        &emsp;&emsp; 95. channel_properties1\\\n",
    "        &emsp;&emsp; 96. channel_properties2\\\n",
    "        &emsp;&emsp; 97. channel_properties3\\\n",
    "        &emsp;&emsp; 98. channel_trig_settings0\\\n",
    "        &emsp;&emsp; 99. channel_trig_settings1\\\n",
    "        &emsp;&emsp; 100. channel_trig_settings2\\\n",
    "        &emsp;&emsp; 101. channel_trig_settings3\\\n",
    "        &emsp;&emsp; 102. Ioff\\\n",
    "        &emsp;&emsp; 103. trace_ch\\\n",
    "    </details>\n",
    "    \n",
    "&emsp;**TRawVoltage:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (33)</summary>\n",
    "        &emsp;&emsp;104. run_number\\\n",
    "        &emsp;&emsp;105. event_number\\\n",
    "        &emsp;&emsp;106. event_size\\\n",
    "        &emsp;&emsp;107. first_du\\\n",
    "        &emsp;&emsp;108. time_seconds\\\n",
    "        &emsp;&emsp;109. time_nanoseconds\\\n",
    "        &emsp;&emsp;110. du_count\\\n",
    "        &emsp;&emsp;111. du_id\\\n",
    "        &emsp;&emsp;112. du_seconds\\\n",
    "        &emsp;&emsp;113. du_nanoseconds\\\n",
    "        &emsp;&emsp;114. trigger_flag\\\n",
    "        &emsp;&emsp;115. atm_temperature\\\n",
    "        &emsp;&emsp;116. atm_pressure\\\n",
    "        &emsp;&emsp;117. atm_humidity\\\n",
    "        &emsp;&emsp;118. du_acceleration\\\n",
    "        &emsp;&emsp;119. battery_level\\\n",
    "        &emsp;&emsp;120. adc_samples_count_channel\\\n",
    "        &emsp;&emsp;121. trigger_pattern\\\n",
    "        &emsp;&emsp;122. trigger_rate\\\n",
    "        &emsp;&emsp;123. clock_tick\\\n",
    "        &emsp;&emsp;124. clock_ticks_per_second\\\n",
    "        &emsp;&emsp;125. gps_offset\\\n",
    "        &emsp;&emsp;126. gps_leap_second\\\n",
    "        &emsp;&emsp;127. gps_status\\\n",
    "        &emsp;&emsp;128. gps_alarms\\\n",
    "        &emsp;&emsp;129. gps_warnings\\\n",
    "        &emsp;&emsp;130. gps_time\\\n",
    "        &emsp;&emsp;131. gps_long\\\n",
    "        &emsp;&emsp;132. gps_lat\\\n",
    "        &emsp;&emsp;133. gps_alt\\\n",
    "        &emsp;&emsp;134. gps_temp\\\n",
    "        &emsp;&emsp;135. ioff\\\n",
    "        &emsp;&emsp;136. trace_ch\\\n",
    "    </details>\n",
    "\n",
    "&emsp;**TVoltage:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (15)</summary>\n",
    "        &emsp;&emsp; 137. run_number\\\n",
    "        &emsp;&emsp; 138. event_number\\\n",
    "        &emsp;&emsp; 139. first_du\\\n",
    "        &emsp;&emsp; 140. time_seconds\\\n",
    "        &emsp;&emsp; 141. time_nanoseconds\\\n",
    "        &emsp;&emsp; 142. du_count\\\n",
    "        &emsp;&emsp; 143. du_id\\\n",
    "        &emsp;&emsp; 144. du_seconds\\\n",
    "        &emsp;&emsp; 145. du_nanoseconds\\\n",
    "        &emsp;&emsp; 146. du_acceleration\\\n",
    "        &emsp;&emsp; 147. trigger_flag\\\n",
    "        &emsp;&emsp; 148. trigger_rate\\\n",
    "        &emsp;&emsp; 149. trace\\\n",
    "        &emsp;&emsp; 150. p2p\\\n",
    "        &emsp;&emsp; 151. time_max\\\n",
    "    </details>\n",
    "        \n",
    "&emsp;**TEfield:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (15)</summary>\n",
    "        &emsp;&emsp; 152. run_number\\\n",
    "        &emsp;&emsp; 153. event_number\\\n",
    "        &emsp;&emsp; 154. time_seconds\\\n",
    "        &emsp;&emsp; 155. time_nanoseconds\\\n",
    "        &emsp;&emsp; 156. event_type\\\n",
    "        &emsp;&emsp; 157. du_count\\\n",
    "        &emsp;&emsp; 158. du_id\\\n",
    "        &emsp;&emsp; 159. du_seconds\\\n",
    "        &emsp;&emsp; 160. du_nanoseconds\\\n",
    "        &emsp;&emsp; 161. trace\\\n",
    "        &emsp;&emsp; 162. fft_mag\\\n",
    "        &emsp;&emsp; 163. fft_phase\\\n",
    "        &emsp;&emsp; 164. p2p\\\n",
    "        &emsp;&emsp; 165. pol\\\n",
    "        &emsp;&emsp; 166. time_max\\\n",
    "    </details>\n",
    "\n",
    "&emsp;**TShower:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (18)</summary>\n",
    "        &emsp;&emsp; 167. run_number\\\n",
    "        &emsp;&emsp; 168. event_number\\\n",
    "        &emsp;&emsp; 169. primary_type\\\n",
    "        &emsp;&emsp; 170. energy_em\\\n",
    "        &emsp;&emsp; 171. energy_primary\\\n",
    "        &emsp;&emsp; 172. azimuth\\\n",
    "        &emsp;&emsp; 173. zenith\\\n",
    "        &emsp;&emsp; 174. direction\\\n",
    "        &emsp;&emsp; 175. shower_core_pos\\\n",
    "        &emsp;&emsp; 176. atmos_model\\\n",
    "        &emsp;&emsp; 177. atmos_model_param\\\n",
    "        &emsp;&emsp; 178. magnetic_field\\\n",
    "        &emsp;&emsp; 179. core_alt\\\n",
    "        &emsp;&emsp; 180. xmax_grams\\\n",
    "        &emsp;&emsp; 181. xmax_pos\\\n",
    "        &emsp;&emsp; 182. xmax_pos_shc\\\n",
    "        &emsp;&emsp; 183. core_time_s\\\n",
    "        &emsp;&emsp; 184. core_time_ns\\\n",
    "    </details>\n",
    "\n",
    "&emsp;**TRunEfieldSim:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (7)</summary>\n",
    "        &emsp;&emsp; 185. run_number\\\n",
    "        &emsp;&emsp; 186. refractivity_model\\\n",
    "        &emsp;&emsp; 187. refractivity_model_parameters\\\n",
    "        &emsp;&emsp; 188. t_pre\\\n",
    "        &emsp;&emsp; 189. t_post\\\n",
    "        &emsp;&emsp; 190. sim_name\\\n",
    "        &emsp;&emsp; 191. sim_version\\\n",
    "    </details>\n",
    "        \n",
    "&emsp;**TRunShowerSim:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (11)</summary>\n",
    "        &emsp;&emsp; 192. run_number\\\n",
    "        &emsp;&emsp; 193. rel_thin\\\n",
    "        &emsp;&emsp; 194. weight_factor\\\n",
    "        &emsp;&emsp; 195. lowe_cut_e\\\n",
    "        &emsp;&emsp; 196. lowe_cut_gamma\\\n",
    "        &emsp;&emsp; 197. lowe_cut_mu\\\n",
    "        &emsp;&emsp; 198. lowe_cut_meson\\\n",
    "        &emsp;&emsp; 199. lowe_cut_nucleon\\\n",
    "        &emsp;&emsp; 200. site\\\n",
    "        &emsp;&emsp; 201. sim_name\\\n",
    "        &emsp;&emsp; 202. sim_version\\\n",
    "    </details>\n",
    "        \n",
    "&emsp;**TShowerSim:**\n",
    "    <details>\n",
    "        <summary>&emsp;&emsp;Click to expand/hide (29)</summary>\n",
    "        &emsp;&emsp; 203. run_number\\\n",
    "        &emsp;&emsp; 204. event_number\\\n",
    "        &emsp;&emsp; 205. input_name\\\n",
    "        &emsp;&emsp; 206. event_date\\\n",
    "        &emsp;&emsp; 207. rnd_seed\\\n",
    "        &emsp;&emsp; 208. sim_primary_energy\\\n",
    "        &emsp;&emsp; 209. sim_primary_type\\\n",
    "        &emsp;&emsp; 210. sim_primary_inj_point_shc\\\n",
    "        &emsp;&emsp; 211. sim_primary_inj_alt_shc\\\n",
    "        &emsp;&emsp; 212. sim_primary_inj_dir_shc\\\n",
    "        &emsp;&emsp; 213. hadronic_model\\\n",
    "        &emsp;&emsp; 214. low_energy_model\\\n",
    "        &emsp;&emsp; 215. cpu_time\n",
    "        &emsp;&emsp; 216. long_depth\\\n",
    "        &emsp;&emsp; 217. long_eminus\\\n",
    "        &emsp;&emsp; 218. long_eplus\\\n",
    "        &emsp;&emsp; 219. long_muminus\\\n",
    "        &emsp;&emsp; 220. long_muplus\\\n",
    "        &emsp;&emsp; 221. long_gammas\\\n",
    "        &emsp;&emsp; 222. long_hadron\\\n",
    "        &emsp;&emsp; 223. long_gamma_elow\\\n",
    "        &emsp;&emsp; 224. long_e_elow\\\n",
    "        &emsp;&emsp; 225. long_e_edep\\\n",
    "        &emsp;&emsp; 226. long_mu_elow\\\n",
    "        &emsp;&emsp; 227. long_mu_edep\\\n",
    "        &emsp;&emsp; 228. long_hadron_elow\\\n",
    "        &emsp;&emsp; 229. long_hadron_edep\\\n",
    "        &emsp;&emsp; 230. long_neutrinos\\\n",
    "        &emsp;&emsp; 231. tested_core_positions\\\n",
    "    </details>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8c28792",
   "metadata": {},
   "source": [
    "### Efield to Voltage\n",
    "\n",
    "An example input ROOT file with electric field traces information is stored in grand/data/. `grand_simu_du.py` is used as an example file to compute voltage from electric-field.\n",
    "\n",
    "You can plot trace and footprint with script `grand_ioroot.py`, the documentation is in grand/scripts/readme.md\n",
    "\n",
    "**Example:**\n",
    "![c2_efieild_du7.png](./c2_efieild_du7.png)\n",
    "\n",
    "### How process Efield data file\n",
    "You can process Efield data with the script `grand_simu_du.py`, the documentation is in grand/script/readme.md\n",
    "\n",
    "```bash\n",
    "/grand/scripts# grand_simu_du.py test_efield.root -o test_voltage.root \n",
    "```\n",
    "\n",
    "**WARNING:**\n",
    "You can't choose the input file as output.\n",
    "\n",
    "You can plot trace and footprint with script `grand_ioroot.py`, the documentation is in grand/script/readme.md, with specific option `--ttree voltage (or efield)`\n",
    "\n",
    "**Example:**\n",
    "![c2_volt_du7.png](./c2_volt_du7.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1f761067",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to JupyROOT 6.26/02\n"
     ]
    }
   ],
   "source": [
    "import grand.dataio.root_files as grf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc61ee9b",
   "metadata": {},
   "source": [
    "The traces are stored in numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cc7f6c42",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(96, 3, 999)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fv = grf.FileEfield(\"/home/grand/data/test_efield.root\")\n",
    "fv.traces.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "16fd602b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f975ee6a550>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot(fv.traces[50, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3a1225f",
   "metadata": {},
   "source": [
    "`FileEfield` is a data class without feature to handle traces. You can use `Handling3dTracesOfEvent()` in grand.basis.traces_event.py to handle traces."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "83e1b3ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "handle_tr = fv.get_obj_handling3dtraces()\n",
    "handle_tr.plot_trace_idx(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1336bc5d",
   "metadata": {},
   "source": [
    "As you can see, this class retrieves the correct unit, the time associated to sample in nanoseconds and allow to use index in array or DU identifier. For example, we can plot trace of DU 7, same plot as above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2fa0a18e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "handle_tr.plot_trace_du(7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6877bcd",
   "metadata": {},
   "source": [
    "You can also, plot footprint with different value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "78eabcad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "handle_tr.plot_footprint_time_max()\n",
    "handle_tr.plot_footprint_val_max()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0bd23a5",
   "metadata": {},
   "source": [
    "If you want learn more on this class, read the docstring with help function in ipython or jupyter notebook:\n",
    "```bash\n",
    "help(handle_tr)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16aabd27",
   "metadata": {},
   "source": [
    "You can use the same technique to plot voltage traces. You have to replace the electric-field file with the voltage file, like `fv = grf.FileEfield(\"/home/grand/data/test_voltage.root\")`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa536a75",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
